Genome-Wide Analysis Reveals Novel Regulators of Growth in Drosophila melanogaster.

Organismal size depends on the interplay between genetic and environmental factors. Genome-wide association (GWA) analyses in humans have implied many genes in the control of height but suffer from the inability to control the environment. Genetic analyses in Drosophila have identified conserved signaling pathways controlling size; however, how these pathways control phenotypic diversity is unclear. We performed GWA of size traits using the Drosophila Genetic Reference Panel of inbred, sequenced lines. We find that the top associated variants differ between traits and sexes; do not map to canonical growth pathway genes, but can be linked to these by epistasis analysis; and are enriched for genes and putative enhancers. Performing GWA on well-studied developmental traits under controlled conditions expands our understanding of developmental processes underlying phenotypic diversity

A novel SNP analysis method to detect copy number alterations with an unbiased reference signal directly from tumor samples

<p>Abstract</p> <p>Background</p> <p>Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples.</p> <p>Methods</p> <p>To address these limitations, we designed a novel "Virtual Normal" algorithm (VN), which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set.</p> <p>Results</p> <p>The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions.</p> <p>Conclusions</p> <p>We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.</p

Fast fluorescence microscopy for imaging the dynamics of embryonic development

Live imaging has gained a pivotal role in developmental biology since it increasingly allows real-time observation of cell behavior in intact organisms. Microscopes that can capture the dynamics of ever-faster biological events, fluorescent markers optimal for in vivo imaging, and, finally, adapted reconstruction and analysis programs to complete data flow all contribute to this success. Focusing on temporal resolution, we discuss how fast imaging can be achieved with minimal prejudice to spatial resolution, photon count, or to reliably and automatically analyze images. In particular, we show how integrated approaches to imaging that combine bright fluorescent probes, fast microscopes, and custom post-processing techniques can address the kinetics of biological systems at multiple scales. Finally, we discuss remaining challenges and opportunities for further advances in this field

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Unlike for Human Monocytes after LPS Activation, Release of TNF-α by THP-1 Cells Is Produced by a TACE Catalytically Different from Constitutive TACE

Tumor necrosis factor-alpha (TNF-α) is a pro-inflammatory cytokine today identified as a key mediator of several chronic inflammatory diseases. TNF-α, initially synthesized as a membrane-anchored precursor (pro-TNF-α), is processed by proteolytic cleavage to generate the secreted mature form. TNF-α converting enzyme (TACE) is currently the first and single protease described as responsible for the inducible release of soluble TNF-α.Here, we demonstrated the presence on THP-1 cells as on human monocytes of a constitutive proteolytical activity able to cleave pro-TNF-α. Revelation of the cell surface TACE protein expression confirmed that the observed catalytic activity is due to TACE. However, further studies using effective and innovative TNF-α inhibitors, as well as a highly selective TACE inhibitor, support the presence of a catalytically different sheddase activity on LPS activated THP-1 cells. It appears that this catalytically different TACE protease activity might have a significant contribution to TNF-α release in LPS activated THP-1 cells, by contrast to human monocytes where the TACE activity remains catalytically unchanged even after LPS activation.On the surface of LPS activated THP-1 cells we identified a releasing TNF-α activity, catalytically different from the sheddase activity observed on human monocytes from healthy donors. This catalytically-modified TACE activity is different from the constitutive shedding activity and appears only upon stimulation by LPS

Brain Struct Funct

Opioid receptors are G protein-coupled receptors (GPCRs) that modulate brain function at all levels of neural integration, including autonomic, sensory, emotional and cognitive processing. Mu (MOR) and delta (DOR) opioid receptors functionally interact in vivo, but whether interactions occur at circuitry, cellular or molecular levels remains unsolved. To challenge the hypothesis of MOR/DOR heteromerization in the brain, we generated redMOR/greenDOR double knock-in mice and report dual receptor mapping throughout the nervous system. Data are organized as an interactive database offering an opioid receptor atlas with concomitant MOR/DOR visualization at subcellular resolution, accessible online. We also provide co-immunoprecipitation-based evidence for receptor heteromerization in these mice. In the forebrain, MOR and DOR are mainly detected in separate neurons, suggesting system-level interactions in high-order processing. In contrast, neuronal co-localization is detected in subcortical networks essential for survival involved in eating and sexual behaviors or perception and response to aversive stimuli. In addition, potential MOR/DOR intracellular interactions within the nociceptive pathway offer novel therapeutic perspectives

Estudios sobre ácidos hidroxámicos: IX. Microreconocimiento y valoración de ácido fórmico y formiatos inorgánicos. Su aplicación a productos alimenticios

Se ha estudiado el reconocimiento y la valoración del ácido fórmico en microcantidades para medios complejos, proponiéndose una técnica sencilla, de rápida ejecución y aplicable a pequeñas cantidades de muestras. El procedimiento se basa en la esterificación del ácido fórmico a formiato de etilo, su destilación, su recepción en solución de hidróxilamina amoniacal para su conversión en ácido formohidroxámico y finalmente su reconocimiento o su valoración fotocolorimétrica como quelato férrico. Se usa un aparato de microdestilación construido con un tubo de ensayos donde se efectúa la esterificación y la destilación simultaneamente, arrastrando los ésteres formados mediante aspiración con aire; se los recoge, previo pasaje por un serpentiín, en un tubo cónico donde se efectúa la hidroxilaminolisis del éster fórmico en condiciones de especificidad. En el mismo tubo se revela la presencia del formohidroxámico por adición de perclorato férrico que desarrolla el color del quelato, apto para ser valorado fotocolorimétricamente. El método permite reconocer 2 μg de ácido fórmico en un volumen final de 4 ml. La valoración fotocolorimétrica se ha adaptado para cantidades entre 50 y 500 μg de ácido fórmico o formiatos inorgánicos. Otros ácidos carboxílicos, α-cetoácidos, aldehidos y glúcidos reductores, no son causa de error. Los casos de mezclas de ácido fórmico, formiatos metalicos y ésteres fórmicos, se resuelven sin dificultad. La valoración del ácido fórmico en diversos productos alimenticios (encurtidos, extracto de carne, extracto de tomate, dulce de leche, dulce de membrillo, embutido, pescado ahumado, miel, vino, zumos de mandarina y limón), muestran tenores variables entre 0 y 45 miligramos por cien gramos de muestra.Facultad de Ciencias Exacta

Estudios sobre ácidos hydroxámicos : III. Microreconocimiento de hidroxilamina como formohidroxamato férrico. Técnicas a la gota y en microtubo

Der in einer fruheren Arbeit beschriebene Nachweis von Hydroxylamin als Eisen(III)hydroxamat kann auch als Tupfelreaktion oder in einer Mikreprouvette ausgefuhrt werden. Die Erfassungsgrenze betragt 0,1 μg Hydroxylamin, die Grenzkonzentration 1∶50000.The detection of hydroxylamin as ferric hydroxamate has been described in a preceding article. Its small-scale performance as spot test and in a small. test tube is described. The limit of identification is 0.1μg hydroxylamine and the limiting concentration is 1∶50000.La recherche de l'hydroxylamine en hydroxamate de fer-III decrite dans un travail anterieur peut etre effectuee aussi sous forme d'analyse a la touche ou en micro-eprouvette. La sensibilite absolue atteint 0,1 μg d'hydroxylamine et la limite de dilution 1∶50000.Facultad de Ciencias Exacta